This talks identifies the high value to researchers in many disciplines of having web-based graphical editors for scientific workflows and draws attention to two technological transitions: good quality editors can now run in a browser and workflow enactment systems are emerging that manage multiple workflow languages and support multi-lingual workflows.

Date and time:

Sunday, 17 November, 2013 - 16:40

Location:

WORKS 2013: 8th Workshop On Workflows in Support of Large-Scale Science, Denver, Colorado, USA

Researchers often need to use workflows that have been developed by other experts in their field to handle specific parts of their work. Sooner or later they find that they want to use workflows from multiple sources that are written in different languages. Enacting multi-lingual workflows (or meta workflows) has been pioneered in a group of European projects. The next step is to be able to change them when they don’t do exactly what you want. But that is not easy if you need to learn a different editor for each workflow language.

Brain imaging researchers execute complex multistep workflows in their computational analysis. Those workflows often include applications that have very different user interfaces and sometimes use different data formats. A good example is the brain perfusion quantification workflow used at the BRIC (Brain Research Imaging Centre) in Edinburgh.

NG Embryo aims to create an educational repository of developmental biology models that is:
- Accessible to researchers, teachers and students
- Searchable via annotated images rather than keywords and free text
- Able to map results onto 3D models of developing embryos
- Updated and enhanced with materials from researchers and lecturers throughout the world
- Free and available online

We show a screencast of a portlet created for Parallel TCoffee—the first parallel implementation of the TCoffee multiple sequence alignment tool. The portlet was developed using our Rapid technology and shows how TCoffee can be run on the UK National Academic Supercomputer HECToR. To see this demo you require Flash to be installed.

A better understanding of the ground beneath our feet will result from research by seismologists and Rapid—a group of computer scientists at the University of Edinburgh. The Earth's structure controls how earthquakes travel and the damage they can cause. A clear picture of this structure would be extremely valuable to earthquake planners, but it requires the analysis of huge amounts of data. The Rapid team developed a system that performs the seismologists' data-crunching, and have made it easy to use by relying on an interface familiar to all scientists – a web browser.

Below a screencast where Rapid was used to develop a portal for the UK-national academic supercomputer HECToR. The portal shows how to setup an advanced compute job involving computational chemistry. You need Flash installed in the browser to watch the video below. Click here for a large version

The inherent limits to the predictability of brittle failure events such as earthquakes and volcanic eruptions are important, unknown, and much debated. We will establish techniques to determine what this limit is in the ideal case of controlled laboratory tests, for the first time in real-time, prospective mode, meaning before failure has occurred.

Develop domain-specific web portals for submitting and managing corresponding compute jobs on the HECToR National Supercomputing Facility (http://www.hector.ac.uk/) in order to reduce the current failure rates and lower the barrier of uptake to new user groups.

Not every user knows how to submit a compute job by a remote login or to adapt to different job- submission systems when switching between facilities. In recognition, a recent trend is to provide web portals as an interface, which come in two types, each with its own major drawback. The first type consists of generic job-submission portals, which still require many technical specifics to be supplied by the user and much manual handling of data and results. The second type consists of domain-specific portals, which are expensive and time-consuming to build and maintain.

Edinburgh Data-Intensive Research Data-intensive refers to huge volumes of data, complex patterns of data integration and analysis, and intricate interactions between data and users. Current methods and tools are failing to address data-intensive challenges effectively. They fail for several reasons, all of which are aspects of scalability.